code: def __init__(
      self,
      theta,
      mu=0.0,
      sigma=1.0,
      dt=1e-2,
      size=1,
      sigma_min=None,
      n_steps_annealing=1000,
  ):
      super(OrnsteinUhlenbeckProcess, self).__init__(
          mu=mu,
          sigma=sigma,
          sigma_min=sigma_min,
          n_steps_annealing=n_steps_annealing,
      )
      self.theta = theta
      self.mu = mu
      self.dt = dt
      self.size = size
      self.reset_states()
  
file_path: keras-rl/rl/random.py
imports: from __future__ import division
  import numpy
label_desc: Use image node_id 1 to create a new OrnsteinUhlenbeckProcess object from inherited base classes: AnnealedGaussianProcess with example: obj = OrnsteinUhlenbeckProcess(theta, mu, sigma, dt, size, sigma_min, n_steps_annealing)